Neural signal processing techniques to analyse motor functions in EEG-based brain-computer interfaces
The electroencephalogram (EEG)-based Brain-Computer Interface (BCI) provides an alternative pathway to transmit neural information to a computer. Nowadays, EEG-based Brain-Computer Interfaces are becoming popular due to the cost-effectiveness, portability, and the high temporal resolution of EEG. Al...
Saved in:
Main Author: | Vikram, Shenoy Handiru |
---|---|
Other Authors: | Vinod Achutavarrier Prasad |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/73334 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Efficient EEG frequency band selection techniques for a robust motor imagery based brain-computer interface
by: Kavitha P. Thomas
Published: (2011) -
Brain-computer interface based on machine learning of the EEG signals
by: May Pwinnt Kyaw Thet
Published: (2020) -
Signal processing and machine learning for recognizing EEG signals of brain-computer interface
by: Yuan, Xinyu
Published: (2021) -
EEG signal analysis using machine learning
by: Zhang, Enshang
Published: (2022) -
Recognizing EEG signals for brain-computer interface based on machine learning
by: Yin, May Lin
Published: (2019)